I work as a fractional product marketer and growth operator for subscription software companies, partnering directly with founders to clarify product positioning, improve conversion across the customer lifecycle, and make revenue performance legible.

Earlier in my career, I led product marketing at a B2B scheduling SaaS where I facilitated a 20% increase in trial-to-paid conversion and ~$700K in incremental ARR over three years. 

Today, I work with a small number of companies at a time, embedding closely with product and engineering to improve clarity, conversion, and retention, especially in situations where growth has plateaued or metrics are difficult to trust.

Former clients include Suno, WAVS, Kits.AI, Neural Frames, Lemonaide, Sesh.fm, NeuTune, Water & Music, ACE Studio, Audio Design Desk, RipX, HookTheory, Samplab, and others.

Ezra Sandzer-Bell

Here’s the New Years Guide to AI Music Generators in Q1 2026, with top companies and reporters to watch.🌟

🦍 Suno: The 800 pound gorilla

$200M ARR in Q4 2025, $2.45B valuation.

Suno scraped volumes of music without a license, claimed fair use in court, and signed a deal with WMG at the end of 2025.

Meanwhile, they've gained first mover advantage and attracted world class talent. SUNO Studio (Suno + WavTool) is the best AI DAW on the market, if we're talking about music quality and software UX.

Suno allows commercial use and grants song ownership to paid users, despite a moment of confusion in December.

 💐 Runners Up: Alternatives to Suno

↝ Udio: High quality AI song generator, trained on unlicensed music just like Suno.

Their AI voice models improved last year, but a new UMG partnership dictates a no download policy that upset their base.

If musicians can't use Udio for stems, and hustlers can't turn AI songs into royalty checks from DSPs, who is Udio selling to?

They might pivot to AI streaming, like KLAY.

↝ ElevenLabs: Single track audio timeline editor. Generates sfx/foley and music from a single prompt. Best for media teams on a limited budget.

↝ Mozart AI: AI DAW and music model hub. Acts as a wrapper for the ElevenLabs model, exposing a multitrack editor and instrument stems. 

↝ Aiode: AI DAW in public beta. Contextual stem generation, static instrument models (think Lemonaide Music but audio instead of MIDI).

↝ Producer.ai (formerly Riffusion): AI chat interface with text to music generation. Songs are generic, UX is clean.

↝ Controlla: AI singing voice company with song generation tool and B2B API.

↝ Moises Studio: Honorable mention. AI DAW with bland, generic audio but decent market visibility due to parent company.

🥷 Stealth companies to watch for in 2026

↝ KLAY: AI streaming service partnering with majors, not launched yet.

↝ MixAudio by Neutune: AI music gen company, specializing in IP attribution for genAI models.

↝ Stability AI's Stable Audio: Open source sample generator, new UMG partnership.

↝ Splice: New partnership with UMG announced at end of year. No details yet about the model or how it might fit into their product ecosystem.

↝ OwlDuet: Voice operated DAW, waitlist only but I was told they’re active.

🙋🏻‍♂️ LinkedIn reporters I follow for AI music industry updates:

1. Christopher Wieduwilt (The AI Musicpreneur) - Weekly news bites
2. Cherie Hu - Founder at Water & Music, deep AI music industry data
3. Kristin Robinson - Investigative journalist with AI music focus at Billboard
4. Virginie Berger - AI music IP attribution expert, Forbes journalist
5. Jordi Pons - AI music research scientist and artist, Stable Audio
6. Rithik Kundu - Founder and event coordinator for NYU's AI music program
7. Mark Redito & John von Seggern - AI music focused podcast hosts
8. Drew Thurlow - Music and AI professor at Berklee, ex Sony/Warner

💫 Follow me here for ongoing AI music news and industry insights.

Music software founder turned fractional PMM. Growth advisor, product manager and copywriter for music tech startups.

Dreamtonics just launched a powerful, ethically-trained AI Choir tool for composers and music producers. 🚀

The new AI choir feature expands on their core standalone app, Synth V Studio Pro 2. 

I'll explain how this all fits into the greater music tech ecosystem below.👇 

🎙️ Dreamtonics: Synth V Pro 2 for musicians

Dreamtonics published the original Synth V software back in 2018. It took them six years and lots of R&D to arrive at version two.

Synth V Pro 2 came out in March 2025, focused on solo voice synthesis. It's a serious musician tool, with a MIDI piano roll and phoneme-level vocal timbre control.

Polyphonic arrangements were *technically* possible in the 2025 version. But stacked, solo vocal stems didn’t deliver the vocal realism of a live choir.

Dreamtonics spent two years researching technical solutions, recording real human choirs (consensually licensed) to train their AI models.

On January 15th, they released three choir voice collections with support for up to 16 vocalists singing in English, Spanish, Japanese, Korean, Mandarin, or Cantonese.

🎹 Better than Suno: Control every note and vocal articulation

Dreamtonics's Synth V Pro 2 outperforms Suno Studio in two major ways; note and timbre control.

Suno does not provide stem-level note manipulation (i.e. autotone). They have a newer audio-to-MIDI feature, but those MIDI notes are divorced from the timbre and lyrics of the original audio file.

Other AI audio-to-midi tool like Hit'n'Mix - RipX or Samplab, or even Celemony Software GmbH's Melodyne Autotune software, let you modify notes in the original audio stem. Suno has not rolled this out yet.

Dreamtonics supports note dictation for custom lyrics AND allows users to edit the pronunciation of every syllable. None of the above audio-to-midi tools support vocal timbre control of this kind.

🗺️ Synth Voices: Mapping the territory

Old school MIDI synth choir patches were limited to vowel tones. Those cheeky "male choir ooh" sounds worked well enough for classic JRPGs and 80s synth ballads, but they're outdated and rarely used anymore.

Modern music software has improved on the timbre of the synth vocals, but are still limited to vowel sounds or random single-word triggers. 

Industry leaders like Spitfire Audio and ARTURIA don't support lyric inputs or phoneme control. They’re ordinary synths.

Choir: Omnia by Native Instruments supports syllable-by-syllable vocal sampling without an AI model, with far less control over notes and pronunciation. 

Choir Omnia costs $400, making it more expensive than Synth V Studio Pro 2 ($99) and a $150 Dreamtonics choir voice collection. 

🥊 TIMEDOMAIN's ACE Studio 2 is the only other AI singing voice DAW that competes with Dreamtonics today. They have a piano roll and AI choir feature.

Controlla and Kits.AI are two simpler, popular AI choir tools for web browser. Controlla is less expensive than Kits and grants users more output minutes per subscription tier.

Fast-forward your online growth and get sh*t done without wasting your time or money. | MarTech Consultant

Hey, I’m Sean.

I’ve helped clients generate over $100 million in revenue by aligning their MarTech, automation, and analytics into systems that run smoother, convert better, and scale faster.

I help fast-moving founders and scaling teams accelerate growth by fixing the tech, data, and marketing chaos that quietly kills momentum.
What I Do:

We start by identifying the friction.
Disconnected tools. Funnels that leak. Campaigns that launch but never scale.

Then I build systems that give you clarity, speed, and consistent results.

This can include:

     - A lean MarTech stack that actually talks to itself
     - Automation that closes leads without follow-up loops
     - Analytics that show what’s working so you can double down
     - SEO support when organic growth fits the model
     - Launch-ready systems for new offers, sites, or campaigns

Who I Work With:

     - Founders scaling from $1M to $20M
     - Startups shifting from founder-led to systems-led growth
     - VC-backed teams racing toward real revenue milestones
     - Operators tired of wasting money on broken marketing

Why Work With Me:

     - I’ve built and broken real systems. I know where the landmines are.
     - I don’t spoon-feed. I make your team faster, sharper, and more focused.
     - I’m built for ROI. You’ll move quicker, spend smarter, and actually trust your growth again.


If you’re scaling and tired of systems that don’t, DM me “SYSTEMS” and I’ll show you how to simplify, streamline, and scale.

      👉 Book your free call now: https://seankoole.com/book/

Sean Warren Koole

This chart explains why traditional SEO thinking is breaking.

Google’s AI Overviews don’t primarily cite:
→ Company blogs
→ Polished brand content
→ “Authority” sites in the classic sense

They overwhelmingly cite:
→ Quora
→ Reddit
→ YouTube
→ LinkedIn

In other words: UGC-heavy platforms dominate AI visibility.

Here’s the strategic implication most teams are missing:

AI systems don’t rank websites.
They rank patterns of explanation.

UGC platforms win because they contain:
→ Repeated questions
→ Multiple explanations of the same concept
→ Natural language disagreement
→ First-person experience
→ Iterative clarification

That’s gold for training and retrieval.

A single perfect article explains once.

A thousand imperfect answers explain from every angle.

That’s why AI trusts them more.

This changes brand strategy:

SEO alone ≠ AI visibility
Publishing alone ≠ memorability
Owning content ≠ being cited

The new shortcut is participation density.

If you want to show up in AI answers:
→ Be present where questions repeat
→ Answer in human language, not brand language
→ Share lived explanations, not frameworks
→ Build recognizable thinking across platforms, not just traffic to one site

The quiet shift happening right now:

Search is moving from indexing pages
to indexing conversations.

Brands that understand this early won’t “optimize for AI.”

They’ll already be where AI is learning.

That’s the advantage.

I solve and uncover complex AI, Marketing, and Tech challenges

Your customers aren’t Googling like they used to.

They’re asking AI.

And AI doesn’t learn from your website first.

It learns from places like:
→ Reddit
→ Wikipedia
→ YouTube
→ Yelp
→ Facebook
→ Amazon
→ LinkedIn

That chart makes one thing obvious:

AI learns from conversations and reviews, not just blogs.

Here’s the simple shift happening:

Before:
👉 “Let’s rank on Google.”

Now:
👉 “Let’s be mentioned where people talk.”

This doesn’t kill SEO.
It expands it.

Because AI doesn’t just find answers.
It recommends them.

And AI recommendations come from:
• discussions
• explanations
• reviews
• real people sharing opinions

That’s why platforms like Reddit and YouTube dominate the list.

So if your brand only exists on:
→ your website
→ your blog

AI is learning about your category without you.

Being found isn’t enough anymore.
Being recommended is what wins.

💾 Save this before planning your 2026 strategy.
📌PS: I help businesses become visible where AI actually learns (not just where Google indexes)

♻️ Repost if someone on your team still thinks SEO ends at Google

If your growth plan is “drive more traffic,”
you’re solving the wrong problem.

Traffic isn’t what’s killing your sales.

Invisibility is.

Your buyers are already researching.
They’re just doing it in places you’re not watching.

The old funnel:
Awareness → Consideration → Purchase.

That’s not how decisions happen anymore.

What actually happens looks like this:
Curiosity → Validation → Skepticism → Comparison → Trust → Impulse

And it all happens:
• across multiple platforms
• at the same time
• sometimes in minutes

Miss one moment → lose the sale.

Here’s where decisions are really being made:

Google → quick intent checks
Reddit → “what do real people think?”
Amazon / TikTok Shop → reviews = confidence
App Stores → ratings = legitimacy
YouTube / Podcasts → long-form trust
AI tools → summarized answers (ChatGPT, Claude)
Instagram / LinkedIn → relevance & credibility

It’s not a funnel.

It’s a decision web.

You don’t need to dominate every platform.

But if you’re invisible where trust is built,
no amount of traffic saves you.

The businesses winning right now aren’t louder.

They’re present at the exact moments decisions happen.

👉 Follow me for simple breakdowns on AI search & modern visibility
♻️ Repost if this changed how you think about growth

PS: Most brands don’t know where they’re invisible until revenue stalls.
I run free AI visibility audits DM me if you want one.

If your growth strategy still depends on “ranking on Google”…
you’re already late.

Not because Google is dead.

But because search no longer lives in one place.

Today, people research by asking:
→ ChatGPT
→ Claude
→ Perplexity
→ voice assistants
→ AI inside browsers, apps, and OSs

And here’s the part most businesses haven’t fully internalized yet:

👉 Google visibility ≠ AI visibility.

LLMs don’t crawl the web the way search engines do.

They synthesize answers from:
→ Reddit discussions
→ Wikipedia entries
→ YouTube transcripts
→ reviews (Amazon, Yelp, TripAdvisor)
→ social platforms (yes, LinkedIn)

This is backed by multiple 2024–2025 studies showing that
user-generated and encyclopedic sources dominate AI citations,
often more than brand-owned websites.

So the shift isn’t theoretical anymore.

It’s already happening.

Here’s the new landscape, simplified:

SEO (Search Engine Optimisation)
→ Ranks pages on Google
→ Click-based traffic
→ Still critical, but slower and more competitive

AEO (Answer Engine Optimisation)
→ Optimises for featured snippets & zero click answers
→ High visibility, fewer guaranteed clicks

GEO (Generative Engine Optimisation)
→ Optimises for AI-generated answers
→ Visibility through mentions and citations
→ Influence without a traditional SERP

And this is the uncomfortable truth:

AI doesn’t rank pages.
It assembles answers.

If your brand isn’t present in the places AI trusts,
it won’t recommend you EVEN if your SEO is strong.

That’s why the companies pulling ahead in 2025 aren’t chasing page-one rankings alone.

They’re making themselves discoverable everywhere people search.

Because content today isn’t just for readers.

It’s training data for the systems people trust to decide.

👉 Follow me for clear, practical frameworks on AI search
💾 Save this it’s a mental model shift you’ll reuse
♻️ Repost if your team still thinks search = Google

📌PS: I help businesses become visible where AI actually learns not just where Google indexes.

Online shopping is about to change.

Google just launched something called the Universal Commerce Protocol (UCP).

Here’s what that means in simple terms 👇

AI can now:
→ help people research products
→ compare options
→ answer questions
→ and complete the purchase

All without sending users to your website.

Think about that.

Your customer could:
• search
• ask follow-up questions
• get recommendations
• apply discounts
• check out

…and soon other platforms.

No cart.
No checkout page.
No abandoned basket.

Google’s goal is simple:
👉 reduce friction
👉 reduce drop-offs
👉 let AI “handle” buying

For shoppers, this feels convenient.

For businesses, this is the shift:

Before:
👉 Get traffic → convert on your site

Now:
👉 Convince AI → close the sale before the site visit

Your website still matters.
But it’s no longer the main decision point.

AI is becoming the front door to commerce.

If your brand isn’t visible, understandable, and trusted inside AI
you’ll be skipped before customers ever see you.

👉 Follow me for simple breakdowns of what AI changes in marketing & commerce

PS: I help businesses stay visible and competitive as AI becomes the new shopping interface.

Google launches Universal Commerce Protocol

8 AI Tools That Actually Save Time in Marketing (2026)

Most marketers don’t have an AI problem.

They have a workflow problem.
They add tools…
but don’t remove work.

Here are 8 AI tools that consistently save 5–20 hours/week when used correctly 👇

1️⃣ ChatGPT / Claude (Strategy, not writing)
❌ Wrong: “Write a LinkedIn post”
✅ Right:
→ Turn messy notes into structured briefs
→ Rewrite content for 5 channels
→ Generate variants for A/B tests

2️⃣ Perplexity (Research replacement)
Replaces:
→ Googling
→ Opening 10 tabs
→ Skimming blogs

Use it for:
→ Market research
→ Competitive analysis
→ Source-backed summaries

3️⃣ Opus Clip / Vidyo (Content repurposing)
Turns:
→ 1 long video
into
→ 10/20 short clips With hooks, captions, framing — automatically.

4️⃣ Gamma (Slides, docs, carousels)
Replaces:
→ Google Slides
→ PowerPoint
→ Canva decks

Use it to:
→ Turn ideas into clean decks
→ Create client-ready docs in minutes

5️⃣ Notion AI (Internal brain)
Best use:
→ Summarizing meetings
→ Updating SOPs
→ Turning chaos into documentation

Not for “writing posts.”
For keeping teams aligned.

6️⃣ Descript (Audio + video editing)
Edit by:
→ Deleting words in text
→ Not scrubbing timelines

Perfect for:
→ Podcasts
→ Talking-head videos

7️⃣ N8N (Automation glue)
Connect:
→ AI outputs
→ To real actions

Examples:
→ AI writes → auto publishes
→ Form filled → AI summarizes → CRM updates

8️⃣ Figma AI (Design acceleration)
Not replacing designers but eliminating first drafts.

Use for:
→ Landing page wireframes
→ Ad creatives
→ Layout exploration

The pattern most people miss:

AI doesn’t save time by being smart.
It saves time by removing transitions.

If you still:
→ Copy
→ Paste
→ Reformat
→ Re explain

You’re underusing it.

If this helped, save it; you’ll come back to it.

And I’m curious 👇
Which one are you already using correctly?

Most people misunderstand how LLMs “decide” what to say.

They assume AI ranks one best page.

It doesn’t.

When you ask a question, LLMs assemble an answer from:
• 8–10 independent sources
• across different formats
• across different domains

Then they look for consensus.

This matters more than rankings.

If AI sees:
• multiple Reddit discussions reviewing the same tools
• YouTube videos comparing competitors
• long-tail blogs mentioning the same brands

It treats that pattern as truth.

Not because it’s perfect.
But because it’s consistent.

Your brand can have:
→ great content
→ strong SEO
→ a polished website

And still be invisible…

If you’re missing from the citation set.

AI doesn’t ask:
“Who has the best landing page?”

It asks:
“Who keeps showing up when this topic is discussed?”

That’s the real ranking layer now.

AI search rewards:
• repetition across sources
• presence in reviews & discussions
• long-tail publishers mentioning you
• multiple perspectives saying the same thing

This is why AI visibility isn’t a content problem.

It’s a distribution problem.

If your competitors dominate the citation pool,
they become the default answer.

Not because they’re better.

Because AI sees them everywhere.

👉 Follow me for frameworks on AI search, GEO, and how visibility really works
💾 Save this it explains why rankings don’t equal recommendations anymore
♻️ Repost if your team still treats SEO as “rank one page”

Most businesses don’t stall because of bad ideas.
They stall because the founder becomes the bottleneck.

That’s the core theme of Friday’s live session with Brett Gilliland.
This isn’t a motivational talk.
It’s a practical breakdown of what actually changes when companies move from:
→ 1M → 3M → 7M → 10M+

Here’s what Brett unpacks (based on real operator experience):

• Why founders get trapped working in the business — and why that stops working at seven figures
• The difference between growth fueled by luck vs growth fueled by systems
• Why chasing sales “peaks” creates false confidence — and consistency creates real confidence
• What it actually means to work on the business (not the buzzword version)
• Why teams treated transactionally behave like mercenaries
• How clear vision (purpose + values + a defined mission) changes execution, ownership, and outcomes

One line from the session that stuck with me:

“People who invest financially want a return.
People who invest emotionally want to contribute.”

That distinction explains:
• team engagement
• leadership burnout
• why some companies scale cleanly — and others don’t

If you’re a founder:
• at seven figures
• feeling constant anxiety
• still central to every decision
• and wondering why growth feels heavier, not easier

This conversation will resonate.

📅 Today — Friday, January 23rd
⏰ 12 PM CST / 7 PM CET
🎙️ Guest: Brett Gilliland

This session is about:
vision, responsibility, systems, and what founders must let go of to scale.

If you’re serious about building a business that doesn’t depend on you forever,
this is worth your time.

👇 Join live and listen closely.

How to Scale a Service Business from 1 Million to 10 Million Revenue?

If you think you’re lucky, your luck will run out.

That’s not pessimism.
That’s business.

At some point, you have to stop relying on:
→ momentum
→ referrals
→ “things just working”

And build something that sells without you.

Because your business is a beast.

And that beast gets hungrier as it grows.

Sales that work at:
• $100k
• $300k
• even $1M

aren’t enough forever.

If sales slow down at scale,
you don’t “feel it.”

You’re immediately in trouble.

That’s why founders get blindsided.

They don’t lose talent.
They don’t lose demand.

They lose fuel.

Luck doesn’t feed the beast.
Systems do.

The biggest content mistake in AI search is treating a blog post as a finished asset.

In reality, a blog post is raw material.

AI systems don’t evaluate content in isolation.

They look for corroboration.

That means:
• explanations repeated in different formats
• answers appearing across platforms
• entities showing up consistently
• users interacting with similar ideas

One well-researched blog can generate at least 8 independent AEO signals:

→ visuals that earn backlinks
→ FAQs that map to prompt space
→ forum answers that create user signals
→ short-form video transcripts
→ entity links feeding the Knowledge Graph
→ audio snippets with schema
→ LinkedIn posts creating co-mentions

This is why some brands keep getting cited by AI
while others keep publishing “great content” and stay invisible.

They’re not writing more.

They’re amplifying the same idea across AI-readable surfaces.

In AI search:
• volume matters less
• consistency matters more
• repetition builds trust

The winning move isn’t “publish faster.”

It’s turning one insight into a signal network.

That’s how 1 blog becomes exponential visibility.

👉 Follow me for frameworks on AI search, AEO, and visibility
💾 Save this it’s how content compounds now
♻️ Repost if your team still treats blogs as one-and-done assets

Affiliate marketing didn’t fail.

You just never learned how it actually works in B2B.

While everyone chased ads, influencers, and “AI growth hacks”…
Affiliate marketing kept doing something boring but powerful:

👉 Printing $10B+ in revenue.

❌No prestige.
❌No hype.
✅Just leverage.

That’s why we’re hosting this live session 👇

Why Affiliate Marketing Is Secretly a $10B+ Growth Machine to A secret $10B+ growth machine!

I’m sitting down with Michael Cole, SVP of Marketing at Everflow - Partner Marketing Platform, to unpack what most B2B teams get completely wrong about affiliates, referrals, and partner growth.

This is not a beginner's talk.
And it’s definitely not “throw up a referral link and hope.”

We’ll break down:

• The hidden scale: tens of billions flowing through affiliate marketing
 • Why affiliate gets no prestige despite massive revenue
 • Turning happy customers into paid referral partners
 • How to structure referral payouts that actually motivate
 • How reviews and affiliate content are evolving with AI
 • What ChatGPT shopping means for affiliates & coupon sites
…and much more.

We’ll also cut through the AI fear.

No job apocalypse.
No affiliate extinction.
Just a shift in how influence, comparison, and trust work.

If you’re a:
• SaaS founder
• Performance marketer
• Partner / ecosystem lead
• Anyone building referrals or partnerships in B2B

This session will change how you think about growth.

📅 Friday, January 16th, 2026
🕛 12 pm CST / 7 pm CET

👉 Save your seat.
👉 Bring someone who still thinks affiliates are “just coupons.”

PS: We’ll also do a live Everflow demo showing how real attribution, payouts, and partner visibility actually work.

Affiliate Marketing is Secretly a $10B+ Growth Machine!

Here’s a hard truth most founders learn too late:

Big wins don’t mean your business is working.

They mean it worked once.

One great Monday can convince you everything’s solved.
Then Tuesday is quiet.
Next month is quiet.

That high is dangerous.

Because it tricks you into chasing peaks instead of building systems.

Real businesses aren’t built on highs.
They’re built on repeatability.

When you consistently close:
• the same number of clients
• every month
• at a size your team can actually handle

Something important happens.

You stop guessing.

That’s when confidence shows up:
• confidence in your product
• confidence in product–market fit
• confidence in your direction
• confidence in your team
• confidence that growth won’t break you

Peaks create stories.
Consistency creates control.

If your growth feels emotional instead of predictable,
this is likely why.

👉 Follow me for grounded insights on building businesses that actually scale
♻️ Repost if you’ve felt this cycle before

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The Battle

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